xlsr_enko_exp2 / README.md
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metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
  - automatic-speech-recognition
  - ./sample_speech.py
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: en-xlsr
    results: []

en-xlsr

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the ./SAMPLE_SPEECH.PY - NA dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5356
  • Cer: 0.0853
  • Wer: 0.1884

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0003
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.01
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Cer Wer
0.7055 2.79 600 0.4911 0.1304 0.3308
0.3761 5.58 1200 0.3984 0.1053 0.2533
0.278 8.37 1800 0.4070 0.1024 0.2445
0.2196 11.16 2400 0.4033 0.0974 0.2243
0.1842 13.95 3000 0.4270 0.0928 0.2106
0.1533 16.74 3600 0.4582 0.0916 0.2071
0.1257 19.53 4200 0.4685 0.0901 0.2001
0.1071 22.33 4800 0.5088 0.0878 0.1965
0.0967 25.12 5400 0.5224 0.0872 0.1913
0.0839 27.91 6000 0.5379 0.0860 0.1885

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.5
  • Tokenizers 0.14.1